Beyond Bilingual Transfer: Multilingual Code-Switching in Instruction Tuning
Researchers demonstrate that multilingual code-switching—mixing multiple languages within training data—improves large language model performance across four languages (English, Japanese, Korean, Chinese) simultaneously, extending previous bilingual findings to truly multilingual settings and showing consistent performance gains on cross-lingual benchmarks.